Research/Original Articles

Niosomal Formulation for Co-Administration of Hydrophobic Anticancer Drugs into MCF-7 Cancer Cells

Iman Akbarzadeh, Mahdi Fatemizadeh, Fatemeh Heidari, Neda Mousavi Niri

Archives of Advances in Biosciences, Vol. 11 No. 2 (2020), 16 May 2020

Introduction: Designing and developing drug delivery systems has received tremendous attention during the last decade. The treatment of cancer cells is a complicated process due to the existence of different biological pathways. Therefore, the co-delivery of different drugs could have a synergic effect on the treatment process.

Materials and Methods: In this study, different types of span (20, 60, 80) and cholesterol were utilized to formulate tamoxifen/curcumin co-loaded niosomes as a drug carrier system for breast cancer chemotherapy. Niosome characterization was performed through a set of instrument analysis techniques including scanning electron microscopy (SEM) and dynamic light scattering. Release behavior was studied by dialysis method at (pH = 5, 7.4). The stability was monitored during two months storage at two temperatures (4 and 25 °C). Cytotoxicity activity of the best niosomal formulation were assessed on MCF-7 cells, using MTT assay.

Results: The optimal niosomal formulation with span 80 and lipid-to-drug molar ratio of 20 was selected, with maximum encapsulation of both drugs and minimum size. Drug release behavior at physiological pH (7.4) (with significant drug release under acidic conditions (pH = 5) and storage stability of up to 2 weeks with little change in drug efficacy and measurement makes it a proper candidate for breast cancer treatment.

Conclusion: Finally, the results of this study showed the importance of creating highly biocompatible formulations, allowing the simultaneous transfer of two drugs with controlled release to cancer cells which could improve the chemotherapy process with the synergistic effect of the two drugs.

Background: Inflammation is basically caused with conversion of Arachidonic acid into Prostaglandin H2 by CycloOxygenase. In this study a new algorithmic procedure is applied in order to screen molecules not only with high affinity to COX-2, but also different from their ancestor compounds.

Methods: NSAIDs, COX-1 and COX-2 molecules were downloaded from Drug Bank and Protein Data Bank. Drugs were docked with both proteins by FlexX software. Top 10 molecules with lowest COX-2 interaction energies and highest differences between COX-2 and COX-1 IEs were selected for structural similarity searches in PUBCHEM and ENCANCED NCI databases. Second generation molecules were docked with proteins once again. Compounds with lower IEs than parents, were collected. Bioactivities and bioavailabilities of compounds were analyzed by PASS software and Lipinski rules. A best multi linear regression model was developed based on some physicochemical descriptors for further studies.

Results: 50 NSAIDs were selected and 2000 similar molecules gathered. Screening the molecules based on Lipinski rules, bioactivities and drug likenesses, a trustable BMLR model was developed with more than 80% accuracy including following descriptors: Log P, Log D, Molar Refractivity, Polarity Number, and Aromaticity Ratio. Finally, 6 compounds were selected as best structurally new compounds for further in vitro analysis.

Conclusions: Final molecules having high druglikeness and affinity and structurally different from their ancestors, can be used in order to develop new lead compounds with higher selectivity.